7/23/2019 MACM316 Syllabus

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MACM 316- Numerical Analysis I

Many computing algorithms used in science and technology are based upon the funda-mental mathematics of calculus and linear algebra. Modern computing environmentsinclude these tools as part of their built-in library of routines. It is essential that usersunderstand these algorithms for purposes of benchmarking implementations, selecting

among multiple variants, and identifying limitations or failure modes. The latter canbe particularly relevant when these algorithms are part of larger complex codes or usedat the extremes of system size.

The aim of this course is to give an overview of the common mathematical algorithmsused in scientific computing, with particular emphasis on connecting their analyticalproperties with their practical performance. Numerical routines will be explored andanalyzed in the context of the three fundamental concerns of scientific computing: ac-curacy, efficiency and robustness.

Students are expected to be comfortable with the pre-requisite mathematics, Calcu-lus and Linear Algebra, and be confident with their programming skills (coding &

debugging). Course assignments will encompass both theory and computation, whichillustrate the ideas presented in lectures, and allow experimentation with numericalroutines. Matlab will be the default computing environment for the class.

Instructor: Sarah Huber, sarah huber@sfu.ca

Lectures: Mon/Wed 10:30-11:20am in WMC 3520, Fri 10:30-11:20am in AQ 3182

Office Hours: Mo 11:30am-12:30pm in SC K9512, Fri 12:30-1:30pm in AQ 4135, or by specialappointment

Tutorials & Workshop Hours: See the Canvas Page

Readings: Numerical Analysis, 9th EditionR.L. Burden & J.D. Faires, Brooks/Cole (2011)

Website: See the Canvas Page

Communication: Canvas will be the main form of class communication and discussion. For per-sonal/urgent matters, please email me directly.

Computing: Matlab will be the primary computing environment. It can be accessed on campus

labs, or you may purchase your own student edition. In-class demos & homework scripts will beposted on Canvas.

Grading Scheme:

Quizzes (20%)

Computing Assignments (20%)

Midterm (20%)

Final Exam (40%)

To be eligible to write the final exam, you must obtain a grade of at least 40% in the computingassignments. Students not meeting this grade will be admitted only at the instructors discretion.